1. Field of the Invention
The present invention relates to graph visualization and more particularly to node filtering when visualizing a large graph.
2. Description of the Related Art
Interlinked data sources such as a graph, also known as a nodal network, are becoming increasingly important for data analytics. Finding unusual structural patterns, or particular combinations of node properties and connections can be vital in areas such as fraud analysis, network optimization, biotech or counter terrorism. Because of their complex nature, visualization of interlinked data sources such as graphs can be critical so as to derive useful information from the interlinked data sources. However, the complexity and size of modern day graphs preclude graphs from being visualized entirely with standard visualization techniques in a limited display space.
In this regard, complexity of a graph can be an important consideration because the number of links in most graphs is such that any item in the graph can be reached in an almost constant number of steps. Trying to manipulate and visualize a large graph with standard node-link based visualization techniques often results in the utilization of substantial memory and bandwidth to retrieve the large graph over a computer communications network, and also the dense, unreadable display of the large graph within a limited display space. To wit, in terms of size, graphs of over several million items are no longer the exception and gaining any amount of insight from exploration alone is a daunting task.
Conventional methods and apparatuses for displaying large graphs within a limited display space are well known. For example, it is known to logically zoom upon a directed graph such that the local structure around a target node can be more readily understood. Thus, it is known in the art, to emphasize within a limited display space only a node of determined interest along with nodes in its immediate logical neighborhood to the detriment of other, less interesting nodes in order to utilize limited display most efficiently for the benefit of the end user. Yet, most current display methodologies rely upon only displaying a contiguous portion of nodes in a large graph and consider only the circumstance where the graph is to be browsed by a single end user.